Reflection

Overview

Now that the 2020 election is officially over and Biden was elected as the President of the United States, it is important that I reflect on my prediction model. I am excited to see how I cold learn from my model for future models that I create.

Model Recap

Let’s first recap on my prediction model to get a better picture of what it was.

• My prediction model was an ensemble model that predicted the popular vote share for each state .

• Given that the Time For Change Model was an inspiration, I decided to focus my model on historical republican vote share as Trump was the incumbent for the 2020 election and incumbency was one predictor in the Time For Change Model.

• I decided to separate America into three categories - red states, blue states, and battleground states - for my model to adjust for overfitting. The grouping were based on how FiveThirtyEight grouped states.

  • Red States - AK, IN, KS, MO, AL, AR, ID, KY, LA, MS, ND, OK, SD, MT, TN, WV, WY, SC, UT, NE
  • Blue States - CO, VA, CA, CT, DE, HI, IL, MD, MA, NJ, NY, OR, RI, VT, WA, ME, NM, NH
  • Battleground states - FL, IA, OH, GA, NC, MI, MN, PA, WI, NV, AZ, TX

• My model used the following data:

  • Historical polling, approval, and turnout data was based on data given from class
  • Historical and present economic data was sourced from the Bureau of Economic Analysis
  • Present polling and approval data was based on FiveThirtyEight’s forecast data

• In my model, I decided to classify approval, Q2 GDP growth, and turnout as fundamentals

• Thus, my ensemble model weighted the poll model (using only polls) by 0.96 and the fundamental model (using only fundamentals) by 0.04 as I weighted the model based on FiveThirtyEight’s reasoning that polls are better predictors as the election nears since fundamentals become more noisy instead.

• My final prediction using the ensemble model was that Biden was projected to win 310 electoral votes while Trump is projected to win 228 votes, meaning Biden would become president-elect of the United States.

Patterns and Accuracy